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What helps an innovation to diffuse?

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Janusz Szwabiński

on 26 May 2017

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Transcript of What helps an innovation to diffuse?

Katarzyna Sznajd-Weron
Our interdysciplinary team
Process, in which
an innovation is communicated
through certain channels over time among the members of a social system
Why diffusion of innovation?
What helps an innovation to diffuse?
Janusz Szwabiński, University of Wrocław

Ideas, products, processes or technologies that are perceived as
NEW
by an individual or other unit of adoption
What is an innovation?
Karol Suszczyński
Piotr Przybyła
K. Sznajd-Weron, J. Szwabiński, R. Weron, T. Weron (2014)
Rewiring the network. What helps an innovation to diffuse?
J. Stat. Mech. 2014 (3) 3007

P. Przybyła, K. Sznajd-Weron, R. Weron (2014) Diffusion of innovation within an agent-based model: Spinsons, independence and advertising, Advances in Complex Systems, in print

P. Nyczka, K. Sznajd-Weron (2013) Anticonformity or independence? – Insights from statistical physics, Journal of Statistical Physics 151, 174-202
Further reading
Meet the spinsons!
Spin + Person = Spinson
Note on Watts-Strogatz model
Piotr Nyczka
Rafał Weron
Anna Kowalska-Pyzalska
Katarzyna Maciejowska
Janusz Szwabiński
Team
Motivation

Model
Results - time evolution
Results
Conclusions
diffusion processes replicate the S-shaped curve of cumulated adopters

topology maters

clustering more important than path length

critical value of external field and critical exponent v depend on topology
Topology: Watts-Strogatz model
Social influence
Independence
: at each time step a spinson takes a purely random opinion with probability
p
, independently of the neighbors and product features
Conformity
: if a spinson is not independent and a group of its neighbors shares an opinion, the spinson will accept it (Sznajd model)
Advertising
: a spinson will become adopted with probability
h
(the strengh of an external field), if it is not independent and not under influence of a group of neighbors
Why diffusion of innovation?

Results - role of topology
Results - role of the mean degree
Results - finite size scaling
Conclusions
Clustering
more important
than path length!!!
The higher the degree the stronger the
influence of the neighbors
=
+
Adopted
Not adopted
Initial conditions
The critical exponent
v
is not universal and
depends on the network topology
construct a regular ring lattice:
N
nodes each connected to
K
neighbors

for every node take every edge and
rewire it
(i.e. replace it by an edge to a randomly chosen node)
with probability
b
Diffusion of hybrid corn in Iowa
(Ryan and Gross, 1943)
The percentage of household penetration for three products in the U.S. (Karl Hartig, 1998)
Full transcript